Sparing land for nature: exploring the potential impact of changes in agricultural yield on the area needed for crop production

How can rapidly growing food demands be met with least adverse impact on nature? Two very different sorts of suggestions predominate in the literature: wildlife‐friendly farming, whereby on‐farm practices are made as benign to wildlife as possible (at the potential cost of decreasing yields); and land‐sparing, in which farm yields are increased and pressure to convert land for agriculture thereby reduced (at the potential cost of decreasing wildlife populations on farmland). This paper is about one important aspect of the land‐sparing idea – the sensitivity of future requirements for cropland to plausible variation in yield increases, relative to other variables. Focusing on the 23 most energetically important food crops, we use data from the Food and Agriculture Organisation (FAO) and the United Nations Population Division (UNPD) to project plausible values for 2050 for population size, diet, yield, and trade, and then look at their effect on the area needed to meet demand for the 23 crops, for the developing and developed worlds in turn. Our calculations suggest that across developing countries, the area under those crops will need to increase very considerably by 2050 (by 23% under intermediate projections), and that plausible variation in average yield has as much bearing on the extent of that expansion as does variation in population size or per capita consumption; future cropland area varies far less under foreseeable variation in the net import of food from the rest of the world. By contrast, cropland area in developed countries is likely to decrease slightly by 2050 (by 4% under intermediate projections for those 23 crops), and will be less sensitive to variation in population growth, diet, yield, or trade. Other contentious aspects of the land‐sparing idea require further scrutiny, but these results confirm its potential significance and suggest that conservationists should be as concerned about future agricultural yields as they are about population growth and rising per capita consumption.     

Do increases in agricultural yield spare land for nature?

Feeding a rapidly expanding human population will require a large increase in the supply of agricultural products during the coming decades. This may lead to the transformation of many landscapes from natural vegetation cover to agricultural land use, unless increases in crop yields reduce the need for new farmland. Here, we assess the evidence that past increases in agricultural yield have spared land for wild nature. We investigated the relationship between the change in the combined energy yield of the 23 most energetically important food crops over the period 1979–1999 and the change in per capita cropland area for 124 countries over the same period. Per capita area of the 23 staple crops tended to decrease in developing countries where large yield increases occurred. However, this was counteracted by a tendency for the area used to grow crops other than staples to increase in the countries where staple crop yields increased. There remained a weak tendency in developing countries for the per capita area of all cropland to decline as staple crop yield increased, a pattern that was most evident in developing countries with the highest per capita food supplies. In developed countries, there was no evidence that higher staple crop yields were associated with decreases in per capita cropland area. This may be because high agricultural subsidies in developed countries override any land-sparing pattern that might otherwise occur. Declines in the area of natural forest were smaller in countries where the yield of staple crops increased most, when the negative effects of human population increases on forest area were controlled for. Our results show that land-sparing is a weak process that occurs under a limited set of circumstances, but that it can have positive outcomes for the conservation of wild nature.     

A review of global potentially available cropland estimates and their consequences for model‐based assessments

The world's population is growing and demand for food, feed, fiber, and fuel is increasing, placing greater demand on land and its resources for crop production. We review previously published estimates of global scale cropland availability, discuss the underlying assumptions that lead to differences between estimates, and illustrate the consequences of applying different estimates in model‐based assessments of land‐use change. The review estimates a range from 1552 to 5131 Mha, which includes 1550 Mha that is already cropland. Hence, the lowest estimates indicate that there is almost no room for cropland expansion, while the highest estimates indicate that cropland could potentially expand to over three times its current area. Differences can largely be attributed to institutional assumptions, i.e. which land covers/uses (e.g. forests or grasslands) are societally or governmentally allowed to convert to cropland, while there was little variation in biophysical assumptions. Estimates based on comparable assumptions showed a variation of up to 84%, which originated mainly from different underlying data sources. On the basis of this synthesis of the assumptions underlying these estimates, we constructed a high, a medium, and a low estimate of cropland availability that are representative of the range of estimates in the reviewed studies. We apply these estimates in a land‐change model to illustrate the consequences on cropland expansion and intensification as well as deforestation. While uncertainty in cropland availability is hardly addressed in global land‐use change assessments, the results indicate a large range of estimates with important consequences for model‐based assessments.     

A large‐area,spatially continuous assessment of land cover map error and its impact on downstream analyses

Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high‐resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel‐wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative “downstream” (map‐based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps’ spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ～45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National‐scale maps derived from higher‐resolution imagery were most accurate, followed by multi‐map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland‐adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%–500% greater than in input cropland maps, but ～40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land cover map users.     

Accuracy assessments of the GLOBCOVER dataset using global statistical inventories and FLUXNET site data

The spatio-temporal distribution of land cover provides fundamental data for global climate and environmental change research. In recent decades, five global land cover maps have been produced based on remote sensing data sources and methodologies. Related research have shown that the availability and quality of the first four global land cover datasets are poor at the regional or the continental scale for a variety of reasons. There is still no consensus on the accuracy of the latest global land cover map. Based on comparison of the land cover dataset with the statistical cropland data from FAO and the FLUXNET site data, this paper discusses the accuracy of the fifth global land cover map, namely, the GLOBCOVER dataset, at different spatial scales. At the global scale, the cropland area obtained from the GLOBCOVER dataset is greater than that of the FAO statistical data by 47.06–84.49%, and the land cover types of the GLOBCOVER dataset have a 65.02% consistency with that of the FLUXNET site data. At the continental scale, the difference between cropland areas obtained from the GLOBCOVER dataset and the statistical cropland area vary from ?43.42% to 502.36%; continents that have a more accurate cropland area compared to the FAO statistical data tend to be less consistent with the FLUXNET site data. In general, North America has a higher accuracy and Oceania has a lower accuracy. At the country scale, the accuracy estimates vary sharply over a wide range: between ?100.00% and 190670.37%. It is recommended that future studies should pay careful attention to the data validation step before using the GLOBCOVER dataset for any particular problem. Future studies are also required for the development of a universal land cover classification system and advanced algorithms for remote sensing classification of global land cover maps.     

Carbon implications of converting cropland to bioenergy crops or forest for climate mitigation: a global assessment

The potential for climate change mitigation by bioenergy crops and terrestrial carbon sinks has been the object of intensive research in the past decade. There has been much debate about whether energy crops used to offset fossil fuel use, or carbon sequestration in forests, would provide the best climate mitigation benefit. Most current food cropland is unlikely to be used for bioenergy, but in many regions of the world, a proportion of cropland is being abandoned, particularly marginal croplands, and some of this land is now being used for bioenergy. In this study, we assess the consequences of land‐use change on cropland. We first identify areas where cropland is so productive that it may never be converted and assess the potential of the remaining cropland to mitigate climate change by identifying which alternative land use provides the best climate benefit: C₄ grass bioenergy crops, coppiced woody energy crops or allowing forest regrowth to create a carbon sink. We do not present this as a scenario of land‐use change – we simply assess the best option in any given global location should a land‐use change occur. To do this, we use global biomass potential studies based on food crop productivity, forest inventory data and dynamic global vegetation models to provide, for the first time, a global comparison of the climate change implications of either deploying bioenergy crops or allowing forest regeneration on current crop land, over a period of 20 years starting in the nominal year of 2000 ad . Globally, the extent of cropland on which conversion to energy crops or forest would result in a net carbon loss, and therefore likely always to remain as cropland, was estimated to be about 420.1 Mha, or 35.6% of the total cropland in Africa, 40.3% in Asia and Russia Federation, 30.8% in Europe‐25, 48.4% in North America, 13.7% in South America and 58.5% in Oceania. Fast growing C₄ grasses such as Miscanthus and switch‐grass cultivars are the bioenergy feedstock with the highest climate mitigation potential. Fast growing C₄ grasses such as Miscanthus and switch‐grass cultivars provide the best climate mitigation option on ≈485 Mha of cropland worldwide with ~42% of this land characterized by a terrain slope equal or above 20%. If that land‐use change did occur, it would displace ≈58.1 Pg fossil fuel C equivalent (C_eq oil). Woody energy crops such as poplar, willow and Eucalyptus species would be the best option on only 2.4% (≈26.3 Mha) of current cropland, and if this land‐use change occurred, it would displace ≈0.9 Pg C_eq oil. Allowing cropland to revert to forest would be the best climate mitigation option on ≈17% of current cropland (≈184.5 Mha), and if this land‐use change occurred, it would sequester ≈5.8 Pg C in biomass in the 20‐year‐old forest and ≈2.7 Pg C in soil. This study is spatially explicit, so also serves to identify the regional differences in the efficacy of different climate mitigation options, informing policymakers developing regionally or nationally appropriate mitigation actions.     

Mapping land cover and forest density in Zagros forests of Khuzestan province in Iran: A study based on Sentinel-2, Google Earth and field data

Zagros forests in western Iran have widely been destroyed because of various reasons. This study was performed to provide the land cover and forest density maps in Zagros forests of Khuzestan province using Sentinel-2, Google Earth and field data. The forest boundary in Khuzestan province was digitized in Google Earth. Sentinel-2 satellite images were provided for the study area. One 1:25000 index sheet of Iranian Mapping Organization (IMO) was selected as pilot area in the province. Sentinel-2 image of the pilot area was classified using different supervised classification algorithms to select the best algorithm for land cover mapping in Khuzestan province. In addition, to evaluate the accuracy of Google Earth data, field sampling was performed using random plots in different land covers. Field data of forest plots were applied to investigate tree canopy cover percent (forest density), as well. Classification of Sentinel-2 image in Zagros area of Khuzestan province was done using the best algorithm and the land cover was obtained. The forest density map was also obtained using a linear regression model between tree canopy cover percent (obtained from field plots) and normalized difference vegetation index (NDVI) (obtained from NDVI map). Finally, the accuracy of land cover map was assessed by some square plots on Google Earth. Results demonstrated that support vector machine (SVM) algorithm had the highest accuracy for land cover mapping. Results also showed that Google Earth images had a good accuracy in the Zagros forests of Khuzestan province. Results demonstrated that NDVI has been a good predicator to estimate tree canopy cover in the study area. Based on results, an area of 443,091.22 ha is covered by Zagros forests in Khuzestan province. Results of accuracy assessment of the land cover map showed the good accuracy of this map in Khuzestan province (overall accuracy: 91% and kappa index: 0.83). For optimum management of Zagros forests, it is suggested that the land cover and forest density mapping will be performed using SVM algorithm, NDVI, and Sentinel-2 satellite images in Zagros forests of Khuzestan province in the certain periods.     

内蒙古奈曼旗农牧交错区土地利用/覆被变化的区域分异

基于内蒙古奈曼旗1975、1985、1995和2005年4期遥感影像,运用土地利用动态度、土地利用相对变化率对研究区土地利用动态变化的区域分异进行了分析,并选取多度和重要值分析了研究区土地利用/覆被变化的空间分布特征.结果表明：1975—2005年间,研究区土地利用/覆被类型趋于多样化,年变化率较大,区域分异显著.研究区北部冲积平原区以林地面积的大幅增加和沙地面积的显著减少为主要特点,其草地和沙地的变化速度最大,居民地的变化速度最小,沙地转化为耕地和沙地转化为林地这两种变化形式在该区的分布最广泛;中部沙区以沙地分布为主,各土地利用类型的变化相对较小,以耕地和沙地的互相转化为该区的主要变化形式;南部黄土区以耕地面积占绝对优势,且变化速度最小,草地和沙地的变化速度最大,该区以草地转化为耕地和草地转化为林地为主要变化形式.自然因素决定了研究区各区域土地利用结构的主体特征,人为因素决定了区域内各土地利用类型的动态变化趋势.     

Land Suitability Assessment on a Watershed of Loess Plateau Using the Analytic Hierarchy Process

In order to reduce soil erosion and desertification, the Sloping Land Conversion Program has been conducted in China for more than 15 years, and large areas of farmland have been converted to forest and grassland. However, this large-scale vegetation-restoration project has faced some key problems (e.g. soil drying) that have limited the successful development of the current ecological-recovery policy. Therefore, it is necessary to know about the land use, vegetation, and soil, and their inter-relationships in order to identify the suitability of vegetation restoration. This study was conducted at the watershed level in the ecologically vulnerable region of the Loess Plateau, to evaluate the land suitability using the analytic hierarchy process (AHP). The results showed that (1) the area unsuitable for crops accounted for 73.3% of the watershed, and the main factors restricting cropland development were soil physical properties and soil nutrients; (2) the area suitable for grassland was about 86.7% of the watershed, with the remaining 13.3% being unsuitable; (3) an area of 3.95 km², accounting for 66.7% of the watershed, was unsuitable for forest. Overall, the grassland was found to be the most suitable land-use to support the aims of the Sloping Land Conversion Program in the Liudaogou watershed. Under the constraints of soil water shortage and nutrient deficits, crops and forests were considered to be inappropriate land uses in the study area, especially on sloping land. When selecting species for re-vegetation, non-native grass species with high water requirements should be avoided so as to guarantee the sustainable development of grassland and effective ecological functioning. Our study provides local land managers and farmers with valuable information about the inappropriateness of growing trees in the study area along with some information on species selection for planting in the semi-arid area of the Loess Plateau.     

Land‐use change affects water recycling in Brazil's last agricultural frontier

Historically, conservation‐oriented research and policy in Brazil have focused on Amazon deforestation, but a majority of Brazil's deforestation and agricultural expansion has occurred in the neighboring Cerrado biome, a biodiversity hotspot comprised of dry forests, woodland savannas, and grasslands. Resilience of rainfed agriculture in both biomes likely depends on water recycling in undisturbed Cerrado vegetation; yet little is known about how changes in land‐use and land‐cover affect regional climate feedbacks in the Cerrado. We used remote sensing techniques to map land‐use change across the Cerrado from 2003 to 2013. During this period, cropland agriculture more than doubled in area from 1.2 to 2.5 million ha, with 74% of new croplands sourced from previously intact Cerrado vegetation. We find that these changes have decreased the amount of water recycled to the atmosphere via evapotranspiration (ET) each year. In 2013 alone, cropland areas recycled 14 km³ less (?3%) water than if the land cover had been native Cerrado vegetation. ET from single‐cropping systems (e.g., soybeans) is less than from natural vegetation in all years, except in the months of January and February, the height of the growing season. In double‐cropping systems (e.g., soybeans followed by corn), ET is similar to or greater than natural vegetation throughout a majority of the wet season (December–May). As intensification and extensification of agricultural production continue in the region, the impacts on the water cycle and opportunities for mitigation warrant consideration. For example, if an environmental goal is to minimize impacts on the water cycle, double cropping (intensification) might be emphasized over extensification to maintain a landscape that behaves more akin to the natural system.     

基于阈值法的山区森林常绿、落叶特征遥感自动识别方法——以贡嘎山地区为例

森林的常绿、落叶特征是土地覆被产品的重要属性。由于山区地形复杂,地表遥感辐射信号地形效应明显,导致山区森林常绿、落叶特征遥感自动识别一直是难点。提出了一种基于阈值法的山区森林常绿、落叶特征遥感自动识别简单实用方法。该方法利用多源、多时相遥感影像,选择归一化植被指数(NDVI)为指标,通过统计参考样本的NDVI在生长季和非生长季的差异,自动找出区分常绿、落叶特征的阈值,基于判别规则识别山区森林常绿、落叶特征。以贡嘎山地区为例,分别以多时相Landsat TM影像(简称TM)、多时相环境减灾卫星影像(简称HJ)为单源数据,多时相的HJ、TM组合影像为多源数据,验证该方法的有效性。实验结果表明,该方法能够有效识别山区森林常绿、落叶特征,总体精度达到93.87%,Kappa系数为0.87。该方法适用于山区大面积森林常绿、落叶特征遥感自动提取,已被成功应用于"生态十年"专项西南地区土地覆被数据的生产。     

Recent collapse of crop belts and declining diversity of US agriculture since 1840

Over the last century, US agriculture greatly intensified and became industrialized, increasing in inputs and yields while decreasing in total cropland area. In the industrial sector, spatial agglomeration effects are typical, but such changes in the patterns of crop types and diversity would have major implications for the resilience of food systems to global change. Here, we investigate the extent to which agricultural industrialization in the United States was accompanied by agglomeration of crop types, not just overall cropland area, as well as declines in crop diversity. Based on county‐level analyses of individual crop land cover area in the conterminous United States from 1840 to 2017, we found a strong and abrupt spatial concentration of most crop types in very recent years. For 13 of the 18 major crops, the widespread belts that characterized early 20th century US agriculture have collapsed, with spatial concentration increasing 15‐fold after 2002. The number of counties producing each crop declined from 1940 to 2017 by up to 97%, and their total area declined by up to 98%, despite increasing total production. Concomitantly, the diversity of crop types within counties plummeted: in 1940, 88% of counties grew >10 crops, but only 2% did so in 2017, and combinations of crop types that once characterized entire agricultural regions are lost. Importantly, declining crop diversity with increasing cropland area is a recent phenomenon, suggesting that corresponding environmental effects in agriculturally dominated counties have fundamentally changed. For example, the spatial concentration of agriculture has important consequences for the spread of crop pests, agrochemical use, and climate change. Ultimately, the recent collapse of most agricultural belts and the loss of crop diversity suggest greater vulnerability of US food systems to environmental and economic change, but the spatial concentration of agriculture may also offer environmental benefits in areas that are no longer farmed.     

Catchment morphometric characteristics,land use and water chemistry in Pampean streams: a regional approach

The Pampean region covers a large surface in central Argentina, but despite the extensive agricultural activities and the high nutrient levels recorded in streams of the region, few authors have analysed the influence of land use on water quality. Here, we evaluated the relationships among catchment attributes (size, morphometry and land cover) and water chemistry in 23 Pampean streams in different seasons (autumn, spring and summer) and at three spatial scales: whole catchment and two scales of riparian buffers (200 and 500 m adjacent to both stream margins). Chloride concentration was positively related to catchment area and negatively related to drainage density. Nitrate level was strongly associated to cropland, but soluble phosphorus concentration showed no relationships with any type of land cover. Land cover at the buffer scale seemed to be more influential than land cover at the whole catchment for nitrogen concentration. The main impact of cropland was the increase of nitrate concentration, while cattle breeding was negatively associated to photosynthetically active radiation (PAR) in autumn and summer and to dissolved oxygen concentration in spring. Our results highlighted the importance of local land use and riparian conservation on streamwater quality.     

A global overview of the conservation status of tropical dry forests

Aim To analyse the conservation status of tropical dry forests at the global scale, by combining a newly developed global distribution map with spatial data describing different threats, and to identify the relative exposure of different forest areas to such threats. Location Global assessment. Methods We present a new global distribution map of tropical dry forest derived from the recently developed MODIS Vegetation Continuous Fields (VCF) product, which depicts percentage tree cover at a resolution of 500 m, combined with previously defined maps of biomes. This distribution map was overlaid with spatial data to estimate the exposure of tropical dry forests to a number of different threats: climate change, habitat fragmentation, fire, human population density and conversion to cropland. The extent of tropical dry forest currently protected was estimated by overlaying the forest map with a global data set of the distribution of protected areas. Results It is estimated that 1,048,700 km² of tropical dry forest remains, distributed throughout the three tropical regions. More than half of the forest area (54.2%) is located within South America, the remaining area being almost equally divided between North and Central America, Africa and Eurasia, with a relatively small proportion (3.8%) occurring within Australasia and Southeast Asia. Overall, c. 97% of the remaining area of tropical dry forest is at risk from one or more of the threats considered, with highest percentages recorded for Eurasia. The relative exposure to different threats differed between regions: while climate change is relatively significant in the Americas, habitat fragmentation and fire affect a higher proportion of African forests, whereas agricultural conversion and human population density are most influential in Eurasia. Evidence suggests that c. 300,000 km² of tropical dry forest now coincide with some form of protected area, with 71.8% of this total being located within South America. Main conclusions Virtually all of the tropical dry forests that remain are currently exposed to a variety of different threats, largely resulting from human activity. Taking their high biodiversity value into consideration, this indicates that tropical dry forests should be accorded high conservation priority. The results presented here could be used to identify which forest areas should be accorded highest priority for conservation action. In particular, the expansion of the global protected area network, particularly in Mesoamerica, should be given urgent consideration.     

Land Use Implications of Increased Biomass Production Identified by GIS-Based Suitability and Yield Mapping for Miscanthus in England

The need for climate change mitigation and to meet increasing energy demands has led to a rise in the land area under bioenergy crops in many countries. There are concerns that such large-scale land conversion will conflict with food production and impact on the environment. Perennial biomass crops could be grown on more marginal agricultural land. However, for sustainable solutions, biomass yields will need to be sufficient and the wider implications of land-use changes considered. Here, focusing on Miscanthus in England as an example, we combined an empirical model with GIS to produce a yield map and estimated regional energy generation potentials after masking out areas covered by environmental and socio-economic factors which could preclude the planting of energy crops. Agricultural land quality and the distributions of currently grown food crops were then taken into account. Results showed that: (i) regional contrasts occur in the importance of different factors affecting biomass planting; (ii) areas with the highest biomass yields co-locate with food producing areas on high grade land, and; (iii) when such high grade land and unsuitable areas are excluded, a policy-related scenario for increased planting on 350,000 ha utilised 4–28% (depending on the region) of lower grade land and would not necessarily greatly impact on UK food security. We conclude that the GIS-based yield and suitability mapping described here can help identify important issues in bioenergy generation potentials and land use implications at regional or finer spatial scales that would be missed in analyses at the national level.     

How willing are landowners to supply land for bioenergy crops in the Northern Great Lakes Region?

Land to produce biomass is essential if the United States is to expand bioenergy supply. Use of agriculturally marginal land avoids the food vs. fuel problems of food price rises and carbon debt that are associated with crop and forestland. Recent remote sensing studies have identified large areas of US marginal land deemed suitable for bioenergy crops. Yet the sustainability benefits of growing bioenergy crops on marginal land only pertain if land is economically available. Scant attention has been paid to the willingness of landowners to supply land for bioenergy crops. Focusing on the northern tier of the Great Lakes, where grassland transitions to forest and land prices are low, this contingent valuation study reports on the willingness of a representative sample of 1124 private, noncorporate landowners to rent land for three bioenergy crops: corn, switchgrass, and poplar. Of the 11% of land that was agriculturally marginal, they were willing to make available no more than 21% for any bioenergy crop (switchgrass preferred on marginal land) at double the prevailing land rental rate in the region. At the same generous rental rate, of the 28% that is cropland, they would rent up to 23% for bioenergy crops (corn preferred), while of the 55% that is forestland, they would rent up to 15% for bioenergy crops (poplar preferred). Regression results identified deterrents to land rental for bioenergy purposes included appreciation of environmental amenities and concern about rental disamenities. In sum, like landowners in the southern Great Lakes region, landowners in the Northern Tier are reluctant to supply marginal land for bioenergy crops. If rental markets existed, they would rent more crop and forestland for bioenergy crops than they would marginal land, which would generate carbon debt and opportunity costs in wood product and food markets.     

中国西南地区土地覆盖情景的时空模拟

气候植被类型的空间分布与土地覆盖类型的空间分布在时空层次上具有很好的相关性和一致性。在运用HLZ生态系统模型获得CMIP5的3种气候情景RCP26、RCP45、RCP85情景下西南地区未来90a(2011—2100年)HLZ生态系统时空分布情景数据的基础上,结合2010年土地覆盖现状数据,构建了土地覆盖情景的空间分析模型,并在此基础上,实现了西南地区未来90a土地覆盖情景的时空模拟分析。模拟结果表明:3种气候情景下,西南地区未来90a的落叶针叶林、落叶阔叶林、草地、耕地、冰雪、荒漠及裸岩石砾地等土地覆盖类型面积将呈逐渐减少趋势;常绿针叶林、常绿阔叶林、混交林、灌丛、湿地、建设用地、水体等土地覆盖类型面积则呈逐渐增加趋势。其中,湿地增加速度最快(平均每10a增加5.28%),荒漠及裸岩石砾地减少速度最快(平均每10a减少2.34%)。     

1990-2011年三峡库区生态系统服务价值演变及驱动力

作为我国西南部重要的生态屏障和生态走廊,三峡库区具有重要的战略意义,其生态问题非常值得关注。研究以覆盖三峡库区的4期Landsat TM遥感影像为数据源,通过人机交互解译分别获得1990、1998、2006、2011年的土地利用/覆盖,参照中国陆地生态系统单位面积生态服务价值当量表,采用研究区单位面积产量与全国农田粮食单位面积产量的比值作为地区修订系数,计算库区生态系统单位面积生态服务价值当量表,同时利用生物量对林地的生态系统服务价值作进一步的修订。然后结合土地利用结构和生态敏感性指数,定量分析土地利用变化引起的生态服系统务价值变化及其驱动因子。结果显示:1990—2011年间,三峡库区生态系统服务价值主要由林地支撑(占76.75%),其次是水域、耕地(共23.19%),草地的贡献率最小(0.22%),总生态系统服务价值从1990年的479.55亿元增加到2011年的680.83亿元;各项服务功能价值中,食物生产功能价值下降,其他各项功能价值上升,以土壤形成与保护功能上升幅度最大,达36.61亿元,其次是气体调节(33.10亿元);驱动力分析表明,库区生态系统服务价值变化的主要原因是人类活动,特别是自1998年实施退耕还林工程以来,各自然生态系统的面积发生较大变化,同时,自然生态系统的健康程度和社会政策对生态系统服务价值变化的影响也不忽可视。研究表明,加强林地、草地和水域等生态系统服价值高的土地利用/覆盖类型保护,是维持库区生态系统稳定性的有效措施。     

Hydrological Response to Land Cover Changes and Human Activities in Arid Regions Using a Geographic Information System and Remote Sensing

The hydrological response to land cover changes induced by human activities in arid regions has attracted increased research interest in recent decades. The study reported herein assessed the spatial and quantitative changes in surface runoff resulting from land cover change in the Al-Baha region of Saudi Arabia between 1990 and 2000 using an ArcGIS-surface runoff model and predicted land cover and surface runoff depth in 2030 using Markov chain analysis. Land cover maps for 1990 and 2000 were derived from satellite images using ArcGIS 10.1. The findings reveal a 26% decrease in forest and shrubland area, 28% increase in irrigated cropland, 1.5% increase in sparsely vegetated land and 0.5% increase in bare soil between 1990 and 2000. Overall, land cover changes resulted in a significant decrease in runoff depth values in most of the region. The decrease in surface runoff depth ranged from 25-106 mm/year in a 7020-km² area, whereas the increase in such depth reached only 10 mm/year in a 243-km² area. A maximum increase of 73 mm/year was seen in a limited area. The surface runoff depth decreased to the greatest extent in the central region of the study area due to the huge transition in land cover classes associated with the construction of 25 rainwater harvesting dams. The land cover prediction revealed a greater than twofold increase in irrigated cropland during the 2000-2030 period, whereas forest and shrubland are anticipated to occupy just 225 km² of land area by 2030, a significant decrease from the 747 km² they occupied in 2000. Overall, changes in land cover are predicted to result in an annual increase in irrigated cropland and dramatic decline in forest area in the study area over the next few decades. The increase in surface runoff depth is likely to have significant implications for irrigation activities.